An improved reliability assessment of a modular robot controller

Abstract

Modular industrial robot systems are well suited for high performance-accuracy, repeatability and speed, or shorter cycle times. Additionally, modular architecture supports flexibility. Modular robot systems are easily adaptable to a wide range of customer applications. A third characteristic of the robot system-reliability-is becoming increasingly important as industrial manufacturing processes and products increase in complexity and the costs associated with robot failure such as production line downtime increase. This project melds new advances in physics of failure science for electrical components with traditional industrial reliability engineering tools. The author develops three modelling approaches for a robot controller drive system. A function block diagram, highlights the main functions in the drive and their interdependencies. Reliability block diagrams estimate the reliability of controller drive system hardware. Finally, a predictive maintainability model is developed to illustrate future use of reliability model results for real-time monitoring in robot service applications. This final model is created by adding physics of failure models at the component level to the system-level reliability models developed earlier in the thesis. The result is twofold. 1) An improved estimate of hardware module reliability and its sensitivity to the selection of components and circuit designs. 2) A new framework to monitor and predict hardware wear-out in real-time. The author identifies simple, quality metrics such as reliability and availability. These metrics are intimately connected to the customer experience. Additionally, this thesis outlays how to translate these customer-driven metrics back into measurable quality targets upstream in the value chain. This creates an integrated approach to quality across the robot system value chain. With these results, this thesis impacts tangible improvements across multiple dimensions: customer satisfaction, field service planning and investment, new product introduction projects, and next generation product design to support industry 4.0.